Biometrics can establish proof-of-identity and to some extent proof of a user's intent to enter into a given transaction. In practical application, the usefulness of biometrics is limited by the precision of the biometric method (captured by false match and false non-match rates) and the quality of the system-level implementation.
One problem with biometric systems is that they can be spoofed, i.e., tricked into accepting something other than the genuine biometric trait. For example, a face-recognition system may be spoofed using a photo. And most fingerprint sensors can be spoofed with fake fingers made from different materials including paper print-outs, rubber, gelatin, silicone, wood glue, etc., particularly when made electrically conductive.
Fingerprint sensors employing the so-called “active thermal principle” are disclosed in U.S. Pat. Nos. 6,091,837 and 7,910,902, both to Ngoc Minh Dinh. The basic principle of the active thermal fingerprint sensor is the use of an array of PIN diodes as thermal sensors to differentiate the ridges and valleys of the human fingerprint since the heat transfer in these two areas are different. (A PIN diode is a diode with a wide, undoped intrinsic semiconductor region between a p-type semiconductor and an n-type semiconductor region. The p-type and n-type regions are typically heavily doped to form ohmic contacts). A typical problem with this kind of device is that latent prints left from a user on the sensor may be scanned and the sensor cannot determine when a real finger is touching the sensor. Liveness detection schemes, i.e., techniques for determining that a live subject is presenting a finger for fingerprint detection, can be used to combat these spoofing techniques and problems with latent prints.
Sensors are typically made by applying the sensing technology to a substrate material. This deposit is then covered with a protective coating. The area of the substrate material surrounding the active sensing area needs to be covered to protect it from the environment (e.g., electro-static-discharge, moisture). Thus, separate liveness detection sensors cannot be placed outside the sensor area.
There a several ways to characterize liveness detection techniques in fingerprint sensors. One way to characterize these techniques is to distinguish in-band methods from methods requiring dedicated liveness detection sensors. In-band methods look at the live image from the fingerprint sensor and try to distinguish features of live fingers which are difficult to replicate in spoofing targets. Static in-band methods look at features smaller than the ridge size, such as pores. Dynamic in-band methods look at how features of live images change over time: for example, the way a finger deforms when it lands on the sensor, or sweat escaping from the ridges as pressure increases. The advantage of in-band methods is that they do not require dedicated hardware. Their main disadvantage is that they are limited by the sensor's spatial and temporal resolution.
Hardware-based liveness detection methods require a dedicated sensor. There are three main methods known to the art. One known method is based on blood oxygenation measurement through pulse oximetry. The method relies on differences in relative absorption between oxygenated and de-oxygenated hemoglobin: oxygenated hemoglobin absorbs more light in the infrared spectrum while de-oxygenated hemoglobin absorbs more light in the red spectrum. Typical blood oxygen monitors work with two LEDs, one with a peak wavelength of 660 nm (red) and one with a peak wavelength near 940 nm (infrared). The ratio of transmitted infrared to red light allows for an estimation of blood oxygenation.
Another technique is based on the so-called blanching effect. The general principle is that when the finger lands on the sensor, blood recedes with increasing pressure and the finger changes in color, i.e., it gets lighter. This technique is described in Hengfoss, et al., “Dynamic Liveness and Forgeries Detection of the Finger Surface on the Basis of Spectroscopy in the 400-1650 nm Region”, Forensic Science International 212 (2011) 61-68, the entirety of which is hereby incorporated by reference herein.
Another known technique is based on laser-doppler flowmetry. This technique uses the Doppler shift effect to detect the movement of blood particles.